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Drawing on social capital theory, this study aims to explore the effect of corporate social responsibility (CSR) on organizational resilience. The research investigates the mediating role of relationship quality in the association of CSR with organizational resilience, and the moderating role of data-driven culture in the association between CSR and relationship quality.

Data were collected from Chinese agricultural firms with a sample of 241 senior or middle executives and structural equation modeling was used to test the research model and hypotheses.

The results indicate that CSR positively affects the relationship quality between agribusinesses and farmers, which in turn positively affects both proactive resilience and reactive resilience. Relationship quality has a partial mediating role in the association of CSR with proactive resilience and reactive resilience. Data-driven culture has a positive moderating effect on the relationship between CSR and relationship quality.

By arguing for CSR toward organizational resilience and analyzing its underlying mechanism, this study enriches the literature on CSR and organizational resilience and expands the existing knowledge on the roles of relationship quality and data-driven culture. This study also provides practical insights into how to improve organizational resilience.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

Neuroscientific research on addictions has prompted a paradigm shift from a moral to a medical understanding – with substantial implications for legal professionals’ interactions with and decision-making surrounding individuals with addiction. This study complements prior work on US defense attorney’s understandings of addiction by investigating two further perspectives: the potential “next generation” of legal professionals in the USA (criminal justice undergraduates) and legal professionals from another system (Germany). This paper aims to assess their views on the brain disease model of addiction, dominance and relevance of this model, the responsibility of affected persons and preferred sources of information.

Views of 74 US criminal justice undergraduate students and 74 German legal professionals were assessed using Likert scales and open-ended questions in an online survey.

Neuroscientific research findings on addictions and views that addiction is a brain disease were rated as significantly more relevant by American students to their potential future work than by German legal professionals. However, a majority of both samples agreed that addiction is a brain disease and that those affected are responsible for their condition and actions. Sources of information most frequently used by both groups were publications in legal academic journals.

In the USA, information for legal professionals needs to be expanded and integrated into the education of its “next generation,” while in Germany it needs to be developed and promoted. Legal academic journals appear to play a primary role in the transfer of research on addiction into legal practice.

This study complements prior work on US defense attorney’s understandings of addiction by investigating two further perspectives.

This research investigates the influence of corporate–NGO collaborations on corporate social responsibility (CSR) disclosure measured in three different ways (i.e. extent, level and quality) in low-income developing economies. Additionally, it examines the moderating effect of corporate profitability in the relationship between corporate–NGO collaborations and CSR disclosure.

This research uses multivariate regression analysis based on data collected from 201 non-financial firms listed on the Pakistan Stock Exchange (PSE).

The findings reveal that corporations with NGO partnerships are more likely to disclose CSR information and provide high-quality information regarding workers, the environment and community-related issues. Further, corporate profitability positively moderates the corporate–NGO collaborations and CSR disclosure relationship.

Research limitations are presented in the conclusion section.

The findings underline the crucial significance of NGOs and their associated normative isomorphism logics for CSR disclosure in low-income countries with weak law enforcement and relatively ineffective state institutions, which were previously believed to lack such institutions.

While some research has suggested that companies in developing countries perceive significant pressure from NGOs to adopt social disclosure, no study has specifically explored how internally driven corporate–NGO collaboration (as opposed to external NGO activist pressures) promotes CSR disclosure specifically in developing economies.

This theoretical paper introduces a conceptual framework for Personal Cultural Heritage Management (PCHM), derived from prior research on migrants' information practices. It elaborates on the literature background and the development of the PCHM framework, highlighting the role of personal information management (PIM) and personal collections in the creation, access and utilization of cultural heritage information.

The study describes and explains the construction of the PCHM framework as a structured and self-motivated approach to personal heritage and identity learning.

Following the theoretical background and assumptions, along with the presentation of the key building blocks, the paper describes the key components of the framework, outlines their definitions and provides examples.

Theoretically, PCHM extends the current literature by encapsulating processes and actions employed by individuals to manage personal collections for cultural identity purposes, thereby underscoring the critical role personal collections play in both preserving and communicating cultural heritage.

PCHM can guide the development of support systems and policies to enhance cultural continuity and integration, thus empowering individuals to navigate their cultural identities confidently.

The PCHM framework creates a unique intersection between PIM and cultural heritage, providing a new perspective for understanding the dynamic evolution and formation of cultural identity among migrants.

Information technology (IT) personnels’ technical, business and behavioral skills are critical enablers for generating IT value. In an increasingly digitalized working environment where non-IT employees participate in digital innovations, a focus on IT personnels’ skills only doesn’t meet researchers’ need for a framework to study digital skills and managers’ need to address digital skills challenges across an enterprise’s workforce. Nevertheless, the digital skills topic is complicated by conceptual ambiguity and a lack of theoretically derived and empirically validated model. The purpose of this study is to address this problem.

Theoretically, this study draws on human capital (HC) and resource-based view (RBV) theories. Empirically, it follows mixed method combining interviews and a survey.

The digital skills construct is a multidimensional second order reflective construct. While its development is influenced by an organization’s commitment and exposure to digitalization, it influences the value organizations obtain from digitalization.

This study conceptualizes the digital skills construct, identifying technology agnostic subdimensions that are meaningful beyond a particular digital domain [information and communication technology (ICT), information, Internet, Inter of Things (IoT)] and establishing a valid measure. Other researchers can improve both the indicators of the existing four conceptually distinct and managerially recognizable workplace digital skills dimensions as well as testing new ones.

Managers can use the instrument to assess the extent to which their non-IT workforces are equipped with digital skills and get strategic insights for specific interventions such as upskilling or buying in skills.

The main theoretical contribution of the paper is the conceptualization and validation of the digital skills construct for the non-IT workforce. Furthermore, we provide a theoretical framework to explain the factors that could influence the development of digital skills and demonstrate the impact that digital skills have on selected digitalization value indicators. This contribution provides the foundation for investigating the drivers, outcomes and the relationship of digital skills to other constructs such as digital transformation, innovation and firm performance.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.

This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field.

The research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI.

This emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection.

The proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies.

This study aims to describe key elements that are critical to virtual qualitative research especially while working with practitioners as participants.

This paper takes a reflexive researcher approach using a case study to explore how researchers adopted a qualitative research approach using digital technology. We use five principles suggested by Boland et al. (2022) as a framework to consider and reflect on our experiences as researchers and those of our participants.

We highlight the gatekeeper’s support, trusted relationship with the organisations, interpersonal skills of interviewers, stringent measures of securing data and shared experiences of interviewee and interviewers helped complete virtual research. We recommend that four key factors such as digital competency, feasibility, flexibility and resilience should be considered while undertaking or commissioning virtual, qualitative research studies.

Social care practitioners and qualitative researchers increasingly negotiate with digital technologies to undertake their work. In this paper, we evidence how online qualitative approaches can be effective provided challenges are dealt with diligently in each stage of the research process.